Zobrazeno 1 - 10
of 12 289
pro vyhledávání: '"P. Shanmugam"'
Publikováno v:
Applied Phycology, Vol 5, Iss 1, Pp 12-23 (2024)
Fucoidan is a naturally occurring sulphate-containing polysaccharide and a major active compound in Turbinaria decurrens, a brown seaweed commonly found in the Indian Ocean. Cancer, particularly lung cancer, poses a huge health burden in terms of inc
Externí odkaz:
https://doaj.org/article/9241f9e066e04316a8b50023772a79f6
Publikováno v:
International Journal of Infectious Diseases, Vol 134, Iss , Pp S2- (2023)
Intro: An increasing number of azole-resistant Candida albicans strains have arisen due to the evolution of acquired resistance and an epidemiological shift toward less vulnerable species. Here we highlight a case of acute pyelonephritis with candide
Externí odkaz:
https://doaj.org/article/677e16c2f2044eb199052efea8ef8346
Autor:
Dasgupta, Arpan, Jain, Gagan, Suggala, Arun, Shanmugam, Karthikeyan, Tambe, Milind, Taneja, Aparna
Mobile health (mHealth) programs face a critical challenge in optimizing the timing of automated health information calls to beneficiaries. This challenge has been formulated as a collaborative multi-armed bandit problem, requiring online learning of
Externí odkaz:
http://arxiv.org/abs/2410.21405
Autor:
Mukherjee, Arpan, Ubaru, Shashanka, Murugesan, Keerthiram, Shanmugam, Karthikeyan, Tajer, Ali
This paper considers the problem of combinatorial multi-armed bandits with semi-bandit feedback and a cardinality constraint on the super-arm size. Existing algorithms for solving this problem typically involve two key sub-routines: (1) a parameter e
Externí odkaz:
http://arxiv.org/abs/2410.10679
Source enumeration, the task of estimating the number of sources from the signal received by the array of antennas, is a critical problem in array signal processing. Numerous methods have been proposed to estimate the number of sources under white or
Externí odkaz:
http://arxiv.org/abs/2409.06563
Language-agnostic many-to-one end-to-end speech translation models can convert audio signals from different source languages into text in a target language. These models do not need source language identification, which improves user experience. In s
Externí odkaz:
http://arxiv.org/abs/2406.10276
Despite the multifaceted recent advances in interventional causal representation learning (CRL), they primarily focus on the stylized assumption of single-node interventions. This assumption is not valid in a wide range of applications, and generally
Externí odkaz:
http://arxiv.org/abs/2406.05937
We introduce the Glauber Generative Model (GGM), a new class of discrete diffusion models, to obtain new samples from a distribution given samples from a discrete space. GGM deploys a discrete Markov chain called the heat bath dynamics (or the Glaube
Externí odkaz:
http://arxiv.org/abs/2405.17035
Autor:
Artman, Conor M., Mate, Aditya, Nwankwo, Ezinne, Heching, Aliza, Idé, Tsuyoshi, Navrátil, Jiří, Shanmugam, Karthikeyan, Sun, Wei, Varshney, Kush R., Goldkind, Lauri, Kroch, Gidi, Sawyer, Jaclyn, Watson, Ian
We developed a common algorithmic solution addressing the problem of resource-constrained outreach encountered by social change organizations with different missions and operations: Breaking Ground -- an organization that helps individuals experienci
Externí odkaz:
http://arxiv.org/abs/2403.10638
This paper addresses intervention-based causal representation learning (CRL) under a general nonparametric latent causal model and an unknown transformation that maps the latent variables to the observed variables. Linear and general transformations
Externí odkaz:
http://arxiv.org/abs/2402.00849